「token-budget」の検索結果

Analyze prompts and offer depth / token-budget options BEFORE answering. Use this skill when the user wants to control token usage, tune response depth, choose between short and long answers, or optimize their prompt. Triggers on: "tokens", "token budget", "depth", "consumption", "short vs long answer", "how many tokens", "save tokens", "answer at 50%", "give me the short version", "I want to control how much you use", "tune your response", "presupuesto de tokens", "profundidad", "responde al 50%", "dame la versión corta", or any equivalent phrasing in English or Spanish. If the user wants to control length, detail or depth -- even without mentioning tokens explicitly -- this skill applies.

日本語の概要は準備中です。原文の説明を表示しています。

回答前に詳しさを4段階で選び、文章量の目安となるトークン数を確認するスキル。短い結論から詳細な解説まで、選んだ水準に合わせて回答を調整します。

• 短い回答と詳しい解説を選びたいとき
• 回答前にトークン数の目安を知りたいとき
• 背景と例を添えた程よい回答がほしいとき

Agent basina token kullanimi takibi, maliyet optimizasyonu, butce limitleri ve ROI analizi. Session ve proje bazinda harcama raporlari. Hangi agent ne kadar token tuketiyor, hangisi verimli, hangisi israf.

日本語の概要は準備中です。原文の説明を表示しています。

Symbol-level code context for LLM coder-agents: tree-sitter extracts symbols, PageRank ranks them over the cross-file reference graph, and the top class/function signatures are fed to the LLM as a token-budgeted read-only map (not RAG, no vector index, human-auditable). Use when an agent must locate the right files in a large/multi-file repo, when builds/refreshes/scopes a repo-map, or when "model edits the wrong file" needs fixing.

日本語の概要は準備中です。原文の説明を表示しています。

Show whether each skill is earning its context-window cost — combined tokens-used view sorted by waste. Use when the user asks 'are my skills worth it', 'what's my context budget', 'which skills are dead weight', or wants to audit skill value, token cost, or usage. Trigger with '/janitor-value'.

日本語の概要は準備中です。原文の説明を表示しています。

Token budget tracking and enforcement for Gastown convoy-level execution. Hard limits with pre-execution checking, per-convoy and per-agent tracking, structured stop reasons.

日本語の概要は準備中です。原文の説明を表示しています。

Monitor, cap, and recover from context accumulation in agentic systems. Covers per-cycle cost tracking, context window auditing, budget caps with enforcement policies, emergency pruning when approaching limits, and progressive disclosure integration to minimize token spend on routing. Use when running long-lived agent loops (heartbeats, polling, autonomous workflows), when context windows are growing unpredictably between cycles, when API costs spike beyond expected baselines, when designing new agentic workflows that need cost guardrails from the start, or when post-mortem analysis reveals a cost incident caused by context accumulation.

日本語の概要は準備中です。原文の説明を表示しています。

Implement a feature phase by phase from a phased JSON master or Markdown plan. Before each phase, confirm whether to create/run unit tests and whether to run ck:quality, unless explicit flags supply those choices. Supports token-budgeted execution, resumable state, and TDD handoff to ck:test.

日本語の概要は準備中です。原文の説明を表示しています。

Implement a feature phase by phase from a phased JSON master or Markdown plan. Before each phase, confirm whether to create/run unit tests and whether to run ck:quality, unless explicit flags supply those choices. Supports token-budgeted execution, resumable state, and TDD handoff to ck:test.

日本語の概要は準備中です。原文の説明を表示しています。

Expert en optimisation des coûts d'agents IA (sélection modèle, caching, compression prompts, budgeting tokens)

日本語の概要は準備中です。原文の説明を表示しています。

Treat tokens as a coding swarm's cost-of-goods-sold and legibility engine while accounting for finite subscription allowance when per-call price is unknown. Covers provider windows, remaining-usage evidence, burn forecasts, preemptive checkpoint/model switching, per-agent budgets, compaction, shared digests, context degradation, and spend metering. Activate on: "token budget", "context budget", "compaction strategy", "briefing as compression", "context rot", "summarization collapse", "COGS for agents", "subscription usage remaining", "five-hour or weekly limit", "burn forecast", "model switch before limit", or "/context-economics-for-agent-swarms". NOT for: memory architecture (use always-on-agent-architecture), single-prompt wording (use prompt-engineer), mechanism-design proofs (use nisan-et-al-2007-algorithmic-game-theory), physical containment (use sandboxed-adversarial-test-harness), or production rebodiment and fencing (use agent-resurrection-and-body-continuity).

日本語の概要は準備中です。原文の説明を表示しています。